Matching‐adjusted indirect comparison of axicabtagene ciloleucel versus mosunetuzumab in relapsed/refractory follicular lymphoma patients after 2 prior systemic treatments
Bibliographic record
Abstract
Introduction: Follicular lymphoma (FL) is an indolent form of non-Hodgkin’s lymphoma; however, relapsed/refractory (R/R) FL patients tend to have poor outcomes. Axicabtagene ciloleucel (axi-cel) was the first chimeric antigen receptor (CAR) T-cell therapy approved for R/R FL patients. More recently, mosunetuzumab was the first bispecific monoclonal antibody approved in R/R FL. We sought to conduct a matching-adjusted indirect comparison (MAIC) to estimate the comparative efficacy and safety of axi-cel and mosunetuzumab for the treatment of 3rd line or higher (3L+) FL. Methods: The evidence base consisted of individual patient data (IPD) from the single-arm axi-cel trial, ZUMA-5, and publications identified through a systematic review pertaining to the mosunetuzumab trial (NCT02500407). For each outcome, prognostic factors—including progression within 24 months of frontline initiation (POD24), refractory status, double refractory, prior stem cell transplant—were a priori identified through quantitative analysis and clinical experts. Outcomes were progression-free survival (PFS), duration of response (DoR), objective response rate (ORR), complete response rate (CRR), and safety. Analyses used independent central review for both trials, where possible. Overall survival (OS) was not analyzed as mosunetuzumab data were immature and not reported in the latest publication. As IPD for axi-cel and aggregate data for mosunetuzumab were available, unanchored MAICs were conducted to align ZUMA-5 to the patient characteristics of the mosunetuzumab trial. Hazard ratios (HRs) from Cox regression were used to compare time-to-event outcomes using pseudo-IPD extracted from published Kaplan-Meier plots for mosunetuzumab and the remaining outcomes were compared using odds ratios (ORs). Index date for ZUMA-5 was date of leukapheresis and included all enrolled patients. Results: Patient characteristics were generally well-aligned between trials leading to large effective-sample sizes after matching, ranging from 99.2 to 109.9, for ZUMA-5 (n = 127). In comparisons to mosunetuzumab (n = 90), axi-cel was associated with improved PFS (HR: 0.38; 95% confidence interval [CI]: 0.23–0.61) and DoR (HR: 0.45; 95% CI: 0.26–0.77). Results were consistent for response outcomes (Figure 1). Sensitivity analyses led to similar results. Although axi-cel was associated with a higher rate of all-grade cytokine release syndrome (CRS) and neurological events (NE), differences in Grade ≥3 (G3+) CRS and treatment-related adverse events (TRAEs) were not statistically significant. Differences in G3+ NE were not evaluable. The research was funded by: Kite, A Gilead Company Keywords: Cellular therapies, Indolent non-Hodgkin lymphoma Conflicts of interests pertinent to the abstract. M. D. Ray Employment or leadership position: Gilead/Kite Stock ownership: Gilead/Kite S. Kanters Employment or leadership position: RainCity Analytics Research funding: RainCity Analytics S. Beygi Employment or leadership position: Gilead/Kite Research funding: Gilead/Kite T. Best Employment or leadership position: Gilead/Kite Stock ownership: Gilead/Kite J. Wulff Employment or leadership position: Gilead/Kite Stock ownership: Gilead/Kite E. H. Limbrick-Oldfield Employment or leadership position: RainCity Analytics A. R. Patel Employment or leadership position: Gilead/Kite Stock ownership: Gilead/Kite O. O. Oluwole Consultant or advisory role: Pfizer, Gilead/Kite, AbbVie, Janssen, TGR Therapeutics, ADC, Novartis, Epizyme, Curio Science, Nektar, Syncopation Honoraria: Pfizer, Gilead
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.014 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".